Enabling Efficient Domain Adaptation via Noise-Enhanced Flow Matching
NoiseFlow is presented, a data-efficient domain adaptation framework that leverages noise-aware modeling and flow matching to enable robust cross-domain generalization and exhibits heterogeneous sensitivity to noise, which can be amplified under domain shift.